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Method use_params

spacy/language.py:1477–1510  ·  view source on GitHub ↗

Replace weights of models in the pipeline with those provided in the params dictionary. Can be used as a contextmanager, in which case, models go back to their original weights after the block. params (dict): A dictionary of parameters keyed by model ID. EXAMPLE:

(self, params: Optional[dict])

Source from the content-addressed store, hash-verified

1475
1476 @contextmanager
1477 def use_params(self, params: Optional[dict]):
1478 """Replace weights of models in the pipeline with those provided in the
1479 params dictionary. Can be used as a contextmanager, in which case,
1480 models go back to their original weights after the block.
1481
1482 params (dict): A dictionary of parameters keyed by model ID.
1483
1484 EXAMPLE:
1485 >>> with nlp.use_params(optimizer.averages):
1486 >>> nlp.to_disk("/tmp/checkpoint")
1487
1488 DOCS: https://spacy.io/api/language#use_params
1489 """
1490 if not params:
1491 yield
1492 else:
1493 contexts = [
1494 pipe.use_params(params) # type: ignore[attr-defined]
1495 for name, pipe in self.pipeline
1496 if hasattr(pipe, "use_params") and hasattr(pipe, "model")
1497 ]
1498 # TODO: Having trouble with contextlib
1499 # Workaround: these aren't actually context managers atm.
1500 for context in contexts:
1501 try:
1502 next(context)
1503 except StopIteration:
1504 pass
1505 yield
1506 for context in contexts:
1507 try:
1508 next(context)
1509 except StopIteration:
1510 pass
1511
1512 @overload
1513 def pipe(

Callers 4

_save_modelFunction · 0.80
save_checkpointFunction · 0.80
trainFunction · 0.80
train_while_improvingFunction · 0.80

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